Principal Software Engineer

Social Finance-posted 2 months ago
$192,000 - $330,000/Yr
Full-time • Senior
San Francisco, CA
Religious, Grantmaking, Civic, Professional, and Similar Organizations
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We are seeking a Principal Software Engineer to join our FROST (Fraud, Risk, Operations and Support Technology) team in Seattle. This role will focus on architecting and building sophisticated fraud detection and anti-money laundering solutions using cutting-edge technologies and data-driven approaches to protect SoFi's members and business.

  • Design and implement advanced fraud detection systems using machine learning models, real-time streaming analytics, and complex event processing.
  • Build comprehensive anti-money laundering solutions including transaction monitoring, customer due diligence (CDD), and suspicious activity reporting systems.
  • Develop sophisticated risk scoring models leveraging Member360 unified data layer and advanced analytics capabilities.
  • Build real-time data pipelines using Apache Kafka, Apache Flink, and AWS Kinesis for processing high-volume transaction streams.
  • Implement ML models using AWS SageMaker, Feature Store, and the Batch Inference Framework for fraud and AML detection.
  • Develop entity relationship analysis using AWS Neptune for investigating complex fraud patterns and money laundering networks.
  • Build operational dashboards and investigative tools using Apache Druid for seconds-fresh fraud and AML analytics.
  • Enhance and optimize SAFE (Security and Fraud Engine) and Flowable rule engines for sophisticated risk decisioning.
  • Architect solutions integrating with fraud detection vendors like DataVisor, Socure, Transmit Security, and Early Warning System (EWS).
  • Build comprehensive fraud and AML investigation platforms within SoFi Atlas for operational efficiency.
  • Bachelor's degree with 15+ years of experience, or Master's degree with 12+ years, or PhD with 8+ years.
  • Extensive experience building fraud detection or AML solutions in financial services.
  • Proven track record with real-time data processing, machine learning, and high-scale distributed systems.
  • Deep understanding of financial crime patterns and regulatory requirements.
  • Expert-level proficiency in programming languages suitable for high-performance financial systems.
  • Deep experience with Apache Kafka, Apache Flink, and real-time event processing architectures.
  • Hands-on experience with AWS SageMaker, Feature Store, and ML model deployment frameworks.
  • Expertise in Snowflake, AWS DynamoDB, and time-series databases for fraud analytics.
  • Experience with AWS Neptune and Gremlin for relationship analysis and investigation workflows.
  • Experience with rule engines like Flowable, Camunda, or similar decisioning platforms.
  • Proficiency with Apache Druid or similar OLAP systems for operational analytics.
  • Experience integrating with fraud detection platforms like DataVisor, identity verification services, and risk data providers.
  • Base pay range: $192,000.00 - $330,000.00
  • Eligible for a bonus and long-term incentives.
  • Comprehensive and competitive benefits.
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